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AMDgpu is an open source device driver for the Linux operating system developed by AMD to support its Radeon lineup of graphics cards (GPUs). It was announced in 2014 as the successor to the previous radeon device driver as part of AMD's new "unified" driver strategy, [3] and was released on April 20, 2015.
In the middle: the FOSS stack, composed out of DRM & KMS driver, libDRM and Mesa 3D.Right side: Proprietary drivers: Kernel BLOB and User-space components. nouveau (/ n uː ˈ v oʊ /) is a free and open-source graphics device driver for Nvidia video cards and the Tegra family of SoCs written by independent software engineers, with minor help from Nvidia employees.
The Direct Rendering Manager (DRM) is a subsystem of the Linux kernel responsible for interfacing with GPUs of modern video cards.DRM exposes an API that user-space programs can use to send commands and data to the GPU and perform operations such as configuring the mode setting of the display.
The main competing factor was the price of hardware and raw performance in 3D computer games, which is greatly affected by the efficient translation of API calls into GPU opcodes. The display driver and the video decoder are inherent parts of the graphics card: hardware designed to assist in the calculations necessary for the decoding of video ...
CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements for the execution of compute kernels. [5] In addition to drivers and runtime kernels, the CUDA platform includes compilers, libraries and developer tools to help programmers accelerate their applications.
Mesa GBM is an abstraction of the graphics driver specific buffer management APIs (for instance the various libdrm_* libraries), implemented internally by calling into the Mesa GPU drivers. For example, the Wayland compositor Weston does its rendering using OpenGL ES 2, which it initializes by calling EGL.
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An example of vainfo output, showing supported video codecs for VA-API acceleration. The main motivation for VA-API is to enable hardware-accelerated video decode at various entry-points (VLD, IDCT, motion compensation, deblocking [5]) for the prevailing coding standards today (MPEG-2, MPEG-4 ASP/H.263, MPEG-4 AVC/H.264, H.265/HEVC, and VC-1/WMV3).